AI DRIVEN HEALTH ADVISOR

ABSTRACT Access to reliable and timely healthcare remains a major challenge in many developing countries, particularly in Nigeria, were limited medical personnel and infrastructure hinder efficient service delivery. This study present the design and implementation of an AI driven Health Advisor System, a web application that utilize artificial intelligence (AI) and Natural Language Processing (NLP) to provide users with intelligent, interactive, and personalized health advice. The system enables users to input symptoms or health-related queries, which are analyzed using a Multiple Naïve Bayes machine learning model trained on verified medical datasets. Base on the analysis, the system generate appropriate response and preventive health recommendations in real time. The application was developed using python, flask, NLTK, Tensor Flow, HTML, CSS, JavaScript, PHP, and MySQL. Evaluation results demonstrated an accuracy of 94% with efficient response time and high usability. The system efficiently bridge the gap between individuals and healthcare services, particularly in underserved regions, by offering immediate, reliable, and evidence-based health guidance. Although it does not replace professional medical consultation, it supports preventive healthcare, reduces misinformation, and enhance access to essential health information. The project validate the potential of AI technologies in promoting equitable healthcare delivery and advancing digital health innovation in Nigeria.